The present invention relates to computing, and in particular, to systems and methods for performing data analysis for model proposals.
In business, academics, government and politics, quick reaction to new situations requires that new information is available in-time. Often this new information is local information from a local source in form of local files, which is external to and not maintained in a central business intelligence or data warehouse. Often the local information needs to be combined with the centrally stored information. The local information is often stored in fields different from the fields of the centrally stored information. Further, the local information may be a different file type with different data fields.
For example, the team lead of a sales department wants to analyze the year-end revenue figures for his highest ranked customers and wants to build special sales teams in his group to address these customers. The revenue figures may come from the data warehouse. The sales department may store the rankings of the customers locally, and not in the data warehouse. Further, the team leader may store locally the grouping of the team members into special year-end sales teams. The grouping may be changed frequently.
One problem associated with combining the data is that the data is stored in different data file formats, with different fields, and with large numbers of data records. It is generally desirable to combine data sets so the data sets can be used collectively. However, the complex data types and concatenations used to create a data mapping model may be difficult for a user that has no or little technical background in query and database management programming tools. Consequently, there exists a need for improved systems and methods for performing data modeling.